Pathway Network Analysis of Complex Diseases Based on Multiple Biological Networks

BioMed Research International
Fang ZhengFuChuan Ni

Abstract

Biological pathways play important roles in the development of complex diseases, such as cancers, which are multifactorial complex diseases that are usually caused by multiple disorders gene mutations or pathway. It has become one of the most important issues to analyze pathways combining multiple types of high-throughput data, such as genomics and proteomics, to understand the mechanisms of complex diseases. In this paper, we propose a method for constructing the pathway network of gene phenotype and find out disease pathogenesis pathways through the analysis of the constructed network. The specific process of constructing the network includes, firstly, similarity calculation between genes expressing data combined with phenotypic mutual information and GO ontology information, secondly, calculating the correlation between pathways based on the similarity between differential genes and constructing the pathway network, and, finally, mining critical pathways to identify diseases. Experimental results on Breast Cancer Dataset using this method show that our method is better. In addition, testing on an alternative dataset proved that the key pathways we found were more accurate and reliable as biological markers of disease. These ...Continue Reading

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Citations

Jul 29, 2021·NAR Cancer·Markus HoffmannMarkus List
Jul 24, 2021·Journal of Biomedical Informatics·A KosvyraI Chouvarda

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Datasets Mentioned

BETA
GSE15852
GSE20437
GSE56807
GSE33335
GSE19826

Methods Mentioned

BETA
xenograft

Software Mentioned

DAVID
SPIA ( Significant Pathway Inference Analysis )
SPIA
DAVID ( Database for Annotation , Visualization and Integrated...
R
GSEA ( Gene Set Enrichment Analysis )
GSEA
GeneRank
Pathologist
SAM

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